Generative AI as a Cognitive Bridging Partner: Applying Adaption–Innovation Theory to Human–AI Collaboration

dc.contributor.authorKaufman, Eric K.en
dc.date.accessioned2026-04-16T14:18:53Zen
dc.date.available2026-04-16T14:18:53Zen
dc.date.issued2026-04-14en
dc.description.abstractAs organizations increasingly integrate generative artificial intelligence (AI) into leadership, education, coaching, and knowledge work, an important question emerges: How might AI interact with or facilitate cognitive style diversity? Kirton’s (2003) Adaption–Innovation (A–I) theory provides a rigorous framework for understanding differences in problem-solving style, structure preference, cognitive gap, and coping behavior (Fridel, 2023). While AI tools are rapidly entering the workplace, they are rarely examined through the lens of cognitive style (Jablokow, 2026). This roundtable proposes that generative AI can be explored not merely as a productivity tool, but as a structured thought partner that may: support Problem A (task resolution), Influence Problem B (managing cognitive diversity), serve as a potential cognitive bridger, and/or affect coping load across wide KAI gaps. The session aligns directly with the 2026 Symposium theme, KAI at 50: Shaping the Future of Work and Wellbeing, by examining how A–I theory can guide responsible and style-aware AI integration in leadership and teamwork contexts. Rather than positioning AI as a replacement for human cognition, this roundtable situates A–I theory as an interpretive framework for understanding and shaping human–AI collaboration.en
dc.description.notesYes, abstract only (Peer reviewed?)en
dc.format.mimetypeapplication/pdfen
dc.identifier.orcidKaufman, Eric [0000-0001-8009-0066]en
dc.identifier.urihttps://hdl.handle.net/10919/143011en
dc.language.isoenen
dc.relation.urihttps://kai.foundation/kai-symposium-2026/en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleGenerative AI as a Cognitive Bridging Partner: Applying Adaption–Innovation Theory to Human–AI Collaborationen
dc.typeConference proceedingen
dc.typePresentationen
dc.type.dcmitypeTexten
pubs.finish-date2026-04-14en
pubs.organisational-groupVirginia Techen
pubs.organisational-groupVirginia Tech/Agriculture & Life Sciencesen
pubs.organisational-groupVirginia Tech/Agriculture & Life Sciences/Agricultural Leadership and Community Educationen
pubs.organisational-groupVirginia Tech/All T&R Facultyen
pubs.organisational-groupVirginia Tech/Agriculture & Life Sciences/CALS T&R Facultyen
pubs.start-date2026-04-13en

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